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Russia-Ukraine war and G7 debt markets: Evidence from public sentiment towards economic sanctions during the conflict

Author

Listed:
  • Zunaidah Sulong

    (Universiti Sultan Zainal Abidin, Malaysia)

  • Mohammad Abdullah

    (Universiti Sultan Zainal Abidin, Malaysia)

  • Emmanuel J. A. Abakah

    (University of Ghana Business School, Accra Ghana)

  • David Adeabah

    (University of Ghana Business School, Accra Ghana)

  • Simplice Asongu

    (Yaoundé, Cameroon)

Abstract

War-related expectations cause changes to investors’ risks and returns preferences. In this study, we examine the implications of war and sanctions sentiment for the G7 countries’ debt markets during the Russia-Ukraine war. We use behavioral indicators across social media, news media, and internet attention to reflect the public sentiment from 1st January 2022 to 20th April 2023. We apply the quantile-on-quantile regression (QQR) and rolling window wavelet correlation (RWWC) methods. The quantile-on-quantile regression results show heterogenous impact on fixed income securities. Specifically, extreme public sentiment has a negative impact on G7 fixed income securities return. The wavelets correlation result shows dynamic correlation pattern among public sentiment and fixed income securities. There is a negative relationship between public sentiment and G7 fixed income securities. The correlation is time-varying and highly event dependent. Our additional analysis using corporate bond data indicates the robustness of our findings. Furthermore, the contagion analysis shows public sentiment significantly influence G7 fixed income securities spillover. Our findings can be of great significance while framing strategies for asset allocation, portfolio performance and risk hedging.

Suggested Citation

  • Zunaidah Sulong & Mohammad Abdullah & Emmanuel J. A. Abakah & David Adeabah & Simplice Asongu, 2023. "Russia-Ukraine war and G7 debt markets: Evidence from public sentiment towards economic sanctions during the conflict," Working Papers 23/057, European Xtramile Centre of African Studies (EXCAS).
    • Handle: RePEc:exs:wpaper:23/057
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    References listed on IDEAS

    as
    1. Umar, Zaghum & Polat, Onur & Choi, Sun-Yong & Teplova, Tamara, 2022. "The impact of the Russia-Ukraine conflict on the connectedness of financial markets," Finance Research Letters, Elsevier, vol. 48(C).
    2. Feng, Chaonan & Han, Liyan & Vigne, Samuel & Xu, Yang, 2023. "Geopolitical risk and the dynamics of international capital flows," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    3. Zaremba, Adam & Kizys, Renatas & Aharon, David Y. & Umar, Zaghum, 2022. "Term spreads and the COVID-19 pandemic: Evidence from international sovereign bond markets," Finance Research Letters, Elsevier, vol. 44(C).
    4. Martina Halouskov'a & Daniel Stav{s}ek & Mat'uv{s} Horv'ath, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Papers 2205.05985, arXiv.org, revised Aug 2022.
    5. Gençay, Ramazan & Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon J., 2001. "An Introduction to Wavelets and Other Filtering Methods in Finance and Economics," Elsevier Monographs, Elsevier, edition 1, number 9780122796708.
    6. Kumari, Vineeta & Kumar, Gaurav & Pandey, Dharen Kumar, 2023. "Are the European Union stock markets vulnerable to the Russia–Ukraine war?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
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    Keywords

    Russia-Ukraine war; economic sanctions; G7 debt; fixed income securities; quantile approaches;
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